NUS ME5413 Autonomous Mobile Robotics Final Project

Origin Authors: Christina, Yuhang, Dongen, and Shuo

Project Group Members: Yuwei, Guorong, Zihan, Jilun, Mingrui, and Peiqi

• System Requirements:
  • Ubuntu 20.04 (18.04 not yet tested)
  • ROS Noetic (Melodic not yet tested)
  • C++11 and above
  • CMake: 3.0.2 and above
• This repo depends on the following standard ROS pkgs:
  • roscpp
  • rospy
  • rviz
  • std_msgs
  • nav_msgs
  • geometry_msgs
  • visualization_msgs
  • tf2
  • tf2_ros
  • tf2_geometry_msgs
  • pluginlib
  • map_server
  • gazebo_ros
  • jsk_rviz_plugins
  • jackal_gazebo
  • jackal_navigation
  • velodyne_simulator
  • teleop_twist_keyboard
  • cv_bridge
  • teb_local_planner
  • navigation
  • find_object_2d
• And this gazebo_model repositiory

This repo is a ros workspace, containing three rospkgs:

• add_obstacle_layer is a plugin to add a custom layer to the costmap
• interactive_tools are customized tools to interact with gazebo and your robot
• jackal_description contains the modified jackal robot model descriptions
• me5413_world the main pkg containing the gazebo world, and the launch files

Note: If you are working on this project, it is encouraged to fork this repository and work on your own fork!

After forking this repo to your own github:

# Clone your own fork of this repo (assuming home here `~/`)
cd
git clone https://github.com/<YOUR_GITHUB_USERNAME>/ME5413_Final_Project.git
cd ME5413_Final_Project

# Install all dependencies
rosdep install --from-paths src --ignore-src -r -y

# Build
catkin_make
# Source 
source devel/setup.bash

To properly load the gazebo world, you will need to have the necessary model files in the ~/.gazebo/models/ directory.

There are two sources of models needed:

• Gazebo official models

  # Create the destination directory
  cd
  mkdir -p .gazebo/models
  
  # Clone the official gazebo models repo (assuming home here `~/`)
  git clone https://github.com/osrf/gazebo_models.git
  
  # Copy the models into the `~/.gazebo/models` directory
  cp -r ~/gazebo_models/* ~/.gazebo/models

• TA‘s customized models

  # Copy the customized models into the `~/.gazebo/models` directory
  cp -r ~/ME5413_Final_Project/src/me5413_world/models/* ~/.gazebo/models

Install the required packages of navigation and template matching:

# Install teb_local_planner
sudo apt-get install ros-noetic-teb-local-planner

# Install find_object_2d
sudo apt-get install ros-noetic-find-object-2d

This command will launch the gazebo with the project world

# Launch Gazebo World together with our robot
roslaunch me5413_world world.launch

After launching Step 0, in the second terminal:

# Launch GMapping
roslaunch me5413_world mapping.launch
# or launch Cartographer
roslaunch me5413_world cartographer.launch
# or launch Fast-lio
roslaunch fast_lio mapping_velodyne.launch

After finishing mapping, run the following command in the thrid terminal to save the map:

# Save the map as `my_map` in the `maps/` folder
roscd me5413_world/maps/
rosrun map_server map_saver -f my_map map:=/map

After completing the mapping task and saving the map, quit all processes and modify the name of the map called in file navigation_test.launch accordingly.

To make sure the script works, you first need to grant permissions to the two Python scripts in the scripts folder：

# Give permision to the scripts
cd ~/ME5413_Final_Project/src/me5413_world/scripts
chmod +x object_position_publisher.py
chmod +x goal_sequence_generator.py

You can now officially run the navigation node, in the first terminal：

# Launch Gazebo World together with our robot
roslaunch me5413_world world.launch

Then, in the second terminal:

# Load a map and launch AMCL localizer
roslaunch me5413_world navigation_test.launch

Robot uses template matching nodes to search and navigate to the target box：

You are welcome contributing to this repo by opening a pull-request

We are following:

• Google C++ Style Guide,
• C++ Core Guidelines,
• ROS C++ Style Guide

We thank Prof. Marcelo and the teaching assistants for their guidance and assistance. We used a lot of ROS open source code in our project and would like to express our gratitude to their authors.

• Cartographer: A collection of mapping algorithms implemented in C++ by Google.
• FAST-LIO: A computationally efficient and robust LiDAR-inertial odometry package by hku-mars group.
• A-LOAM: A collection of robotics algorithms implemented in Python.
• find_object_2d: An integrated visual algorithm library for easy object detection.

The ME5413_Final_Project is released under the MIT License